Customizing the coefficients of urban domestic pollutant discharge and their driving mechanisms: Evidence from the Taihu Basin, China

Abstract

Discharge of urban domestic pollution has risen sharply during China's extensive urbanization. Together with understanding the complexity of influencing factors underpinning this rise, it has become a pressing issue to estimate total discharge and illustrate its driving mechanism scientifically. This paper reports on the monitoring of discharge from 36 sampling sites in selected residential districts in the heavily polluted Taihu Basin, China. The data were used to estimate the total amount of discharge, to develop corresponding urban domestic pollutant discharge coefficients and to analyse associated spatial patterns. Data from a questionnaire survey of over 1000 households in downtown, suburb and market town areas were then used to apply an econometric model in order to distinguish driving mechanisms. The urban domestic pollutant discharge coefficients developed in this paper are generally smaller than those reported nationally for China, based on more generalised data, decaying from city centres to the urban periphery. This study quantifies the amount of discharge and also demonstrates that urban domestic pollutant discharge is driven by multiple factors. For example, urban domestic pollution discharge rates were positively correlated with income and female-dominated households also tend to discharge more wastewater. Other factors were found to have negative correlations, such as sewage treatment rates, awareness of environmental protection, age and degree of education. As well as providing new and refined data on urban pollution discharge characteristics, the research in this paper also demonstrates the utility of combining household questionnaire and sample monitoring data in order to yield greater insights into the causes of typical polluting behaviour in Chinese neighbourhoods.

Keywords: Discharge coefficient; Heavily polluted area; Urban domestic pollution; Water pollution.